Scott A. Jackson

An FDA bioinformatics tool for microbial genomics research on molecular characterization of bacterial foodborne pathogens using microarrays

BackgroundAdvances in microbial genomics and bioinformatics are offering greater insights into the emergence and spread of foodborne pathogens in outbreak scenarios. The Food and Drug Administration (FDA) has developed a genomics tool, ArrayTrackTM, which provides extensive functionalities to manage, analyze, and interpret genomic data for mammalian species. ArrayTrackTM has been widely adopted by the research community and used for pharmacogenomics data review in the FDA’s Voluntary Genomics Data Submission program.ResultsArrayTrackTM has been extended to manage and analyze genomics data from bacterial pathogens of human, animal, and food origin. It was populated with bioinformatics data from public databases such as NCBI, Swiss-Prot, KEGG Pathway, and Gene Ontology to facilitate pathogen detection and characterization. ArrayTrackTM’s data processing and visualization tools were enhanced with analysis capabilities designed specifically for microbial genomics including flag-based hierarchical clustering analysis (HCA), flag concordance heat maps, and mixed scatter plots. These specific functionalities were evaluated on data generated from a custom Affymetrix array (FDA-ECSG) previously developed within the FDA. The FDA-ECSG array represents 32 complete genomes of Escherichia coli and Shigella. The new functions were also used to analyze microarray data focusing on antimicrobial resistance genes from Salmonella isolates in a poultry production environment using a universal antimicrobial resistance microarray developed by the United States Department of Agriculture (USDA).ConclusionThe application of ArrayTrackTM to different microarray platforms demonstrates its utility in microbial genomics research, and thus will improve the capabilities of the FDA to rapidly identify foodborne bacteria and their genetic traits (e.g., antimicrobial resistance, virulence, etc.) during outbreak investigations. ArrayTrackTM is free to use and available to public, private, and academic researchers at http://www.fda.gov/ArrayTrack.

Investigating the global genomic diversity of Escherichia coli using a multi-genome DNA microarray platform with novel gene prediction strategies

BackgroundThe gene content of a diverse group of 183 unique Escherichia coli and Shigella isolates was determined using the Affymetrix GeneChip®E. coli Genome 2.0 Array, originally designed for transcriptome analysis, as a genotyping tool. The probe set design utilized by this array provided the opportunity to determine the gene content of each strain very accurately and reliably. This array constitutes 10,112 independent genes representing four individual E. coli genomes, therefore providing the ability to survey genes of several different pathogen types. The entire ECOR collection, 80 EHEC-like isolates, and a diverse set of isolates from our FDA strain repository were included in our analysis.ResultsFrom this study we were able to define sets of genes that correspond to, and therefore define, the EHEC pathogen type. Furthermore, our sampling of 63 unique strains of O157:H7 showed the ability of this array to discriminate between closely related strains. We found that individual strains of O157:H7 differed, on average, by 197 probe sets. Finally, we describe an analysis method that utilizes the power of the probe sets to determine accurately the presence/absence of each gene represented on this array.ConclusionsThese elements provide insights into understanding the microbial diversity that exists within extant E. coli populations. Moreover, these data demonstrate that this novel microarray-based analysis is a powerful tool in the field of molecular epidemiology and the newly emerging field of microbial forensics.

Chips and SNPs, bugs and thugs: a molecular sleuthing perspective.

Recent events both here and abroad have focused attention on the need for ensuring a safe and secure food supply. Although much has been written about the potential of particular select agents in bioterrorism, we must consider seriously the more mundane pathogens, especially those that have been implicated previously in foodborne outbreaks of human disease, as possible agents of bioterrorism. Given their evolutionary history, the enteric pathogens are more diverse than agents such as Bacillus anthracis, Francisella tularensis, or Yersinia pestis. This greater diversity, however, is a double-edged sword; although diversity affords the opportunity for unequivocal identification of an organism without the need for whole-genome sequencing, the same diversity can confound definitive forensic identification if boundaries are not well defined. Here, we discuss molecular approaches used for the identification of Salmonella enterica, Escherichia coli, and Shigella spp. and viral pathogens and discuss the utility of these approaches to the field of microbial molecular forensics.

High density microarray analysis reveals new insights into genetic footprints of Listeria monocytogenes strains involved in listeriosis outbreaks.

Listeria monocytogenes, a foodborne bacterial pathogen, causes invasive and febrile gastroenteritis forms of listeriosis in humans. Both invasive and febrile gastroenteritis listeriosis is caused mostly by serotypes 1/2a, 1/2b and 4b strains. The outbreak strains of serotype 1/2a and 4b could be further classified into several epidemic clones but the genetic bases for the diverse pathophysiology have been unsuccessful. DNA microarray provides an important tool to scan the entire genome for genetic signatures that may distinguish the L. monocytogenes strains belonging to different outbreaks. We have designed a pan-genomic microarray chip (Listeria GeneChip) containing sequences from 24 L. monocytogenes strains. The chip was designed to identify the presence/absence of genomic sequences, analyze transcription profiles and identify SNPs. Analysis of the genomic profiles of 38 outbreak strains representing 1/2a, 1/2b and 4b serotypes, revealed that the strains formed distinct genetic clusters adhering to their serotypes and epidemic clone types. Although serologically 1/2a and 1/b strains share common antigenic markers microarray analysis revealed that 1/2a strains are further apart from the closely related 1/2b and 4b strains. Within any given serotype and epidemic clone type the febrile gastroenteritis and invasive strains can be further distinguished based on several genetic markers including large numbers of phage genome, and intergenic sequences. Our results showed that the microarray-based data can be an important tool in characterization of L. monocytogenes strains involved in both invasive and gastroenteritis outbreaks. The results for the first time showed that the serotypes and epidemic clones are based on extensive pan-genomic variability and the 1/2b and 4bstrains are more closely related to each other than the 1/2a strains. The data also supported the hypothesis that the strains causing these two diverse outbreaks are genotypically different and this finding might be important in understanding the pathophysiology of this organism.

Molecular applications for identifying microbial pathogens in the post-9/11 era.

Rapid advances in molecular and optical technologies over the past 10 years have dramatically impacted the way biologic research is conducted today. Examples include microarrays, capillary sequencing, optical mapping and real-time sequencing (Pyrosequencing). These technologies are capable of rapidly delivering massive amounts of genetic information and are becoming routine mainstays of many laboratories. Fortunately, advances in scientific computing have provided the enormous computing power necessary to analyze these enormous data sets. The application of molecular technologies should prove useful to the burgeoning field of microbial forensics. In the post-9/11 era, when securing America’s food supply is a major endeavor, the need for rapid identification of microbes that accidentally or intentionally find their way into foods is apparent. The principle that distinguishes a microbial forensic investigation from a molecular epidemiology study is that a biocrime has been committed. If proper attribution is to be attained, a link must be made between a particular microbe in the food and the perpetrator who placed it there. Therefore, the techniques used must be able to discriminate individual isolates of a particular microbe. A battery of techniques in development for distinguishing individual isolates of particular foodborne pathogens is discussed.

Rapid Genomic-Scale Analysis of Escherichia coli O104:H4 by Using High-Resolution Alternative Methods to Next-Generation Sequencing

ABSTRACT Two technologies, involving DNA microarray and optical mapping, were used to quickly assess gene content and genomic architecture of recent emergent Escherichia coli O104:H4 and related strains. In real-time outbreak investigations, these technologies can provide congruent perspectives on strain, serotype, and pathotype relationships. Our data demonstrated clear discrimination between clinically, temporally, and geographically distinct O104:H4 isolates and rapid characterization of strain differences.

FDA Escherichia coli Identification (FDA-ECID) Microarray: a Pangenome Molecular Toolbox for Serotyping, Virulence Profiling, Molecular Epidemiology, and Phylogeny

ABSTRACT Most Escherichia coli strains are nonpathogenic. However, for clinical diagnosis and food safety analysis, current identification methods for pathogenic E. coli either are time-consuming and/or provide limited information. Here, we utilized a custom DNA microarray with informative genetic features extracted from 368 sequence sets for rapid and high-throughput pathogen identification. The FDA Escherichia coli Identification (FDA-ECID) platform contains three sets of molecularly informative features that together stratify strain identification and relatedness. First, 53 known flagellin alleles, 103 alleles of wzx and wzy, and 5 alleles of wzm provide molecular serotyping utility. Second, 41,932 probe sets representing the pan-genome of E. coli provide strain-level gene content information. Third, approximately 125,000 single nucleotide polymorphisms (SNPs) of available whole-genome sequences (WGS) were distilled to 9,984 SNPs capable of recapitulating the E. coli phylogeny. We analyzed 103 diverse E. coli strains with available WGS data, including those associated with past foodborne illnesses, to determine robustness and accuracy. The array was able to accurately identify the molecular O and H serotypes, potentially correcting serological failures and providing better resolution for H-nontypeable/nonmotile phenotypes. In addition, molecular risk assessment was possible with key virulence marker identifications. Epidemiologically, each strain had a unique comparative genomic fingerprint that was extended to an additional 507 food and clinical isolates. Finally, a 99.7% phylogenetic concordance was established between microarray analysis and WGS using SNP-level data for advanced genome typing. Our study demonstrates FDA-ECID as a powerful tool for epidemiology and molecular risk assessment with the capacity to profile the global landscape and diversity of E. coli. IMPORTANCE This study describes a robust, state-of-the-art platform developed from available whole-genome sequences of E. coli and Shigella spp. by distilling useful signatures for epidemiology and molecular risk assessment into one assay. The FDA-ECID microarray contains features that enable comprehensive molecular serotyping and virulence profiling along with genome-scale genotyping and SNP analysis. Hence, it is a molecular toolbox that stratifies strain identification and pathogenic potential in the contexts of epidemiology and phylogeny. We applied this tool to strains from food, environmental, and clinical sources, resulting in significantly greater phylogenetic and strain-specific resolution than previously reported for available typing methods.

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and “genomic signature recognition” approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

Genomic Evidence Reveals Numerous Salmonella enterica Serovar Newport Reintroduction Events in Suwannee Watershed Irrigation Ponds

ABSTRACT Our previous work indicated a predominance (56.8%) of Salmonella enterica serovar Newport among isolates recovered from irrigation ponds used in produce farms over a 2-year period (B. Li et al., Appl Environ Microbiol 80:6355–6365, http://dx.doi.org/10.1128/AEM.02063-14). This observation provided a valuable set of metrics to explore an underaddressed issue of environmental survival of Salmonella by DNA microarray. Microarray analysis correctly identified all the isolates (n = 53) and differentiated the S. Newport isolates into two phylogenetic lineages (S. Newport II and S. Newport III). Serovar distribution analysis showed no instances where the same serovar was recovered from a pond for more than a month. Furthermore, during the study, numerous isolates with an indistinguishable genotype were recovered from different ponds as far as 180 km apart for time intervals as long as 2 years. Although isolates within either lineage were phylogenetically related as determined by microarray analysis, subtle genotypic differences were detected within the lineages, suggesting that isolates in either lineage could have come from several unique hosts. For example, strains in four different subgroups (A, B, C, and D) possessed an indistinguishable genotype within their subgroups as measured by gene differences, suggesting that strains in each subgroup shared a common host. Based on this comparative genomic evidence and the spatial and temporal factors, we speculated that the presence of Salmonella in the ponds was likely due to numerous punctuated reintroduction events associated with several different but common hosts in the environment. These findings may have implications for the development of strategies for efficient and safe irrigation to minimize the risk of Salmonella outbreaks associated with fresh produce.

Exploring genotypic and phenotypic diversity of microbes using microarray approaches.

Application of genome-scale analysis like DNA microarray technology has revolutionized multiple scientific disciplines. Herein, a next generation of DNA microarrays, a DNA tiling approach that allows high throughput sampling of genomes with single-nucleotide precision, is described. As methods revealing a genomic scale examination of cellular phenotypes offer keen insights for genomic analyses, a high throughput system for whole cell phenotyping is similarly detailed. The merit of these technologies in discriminating pathogenic and commensal strains of microbes is emphasized using the microbe, Escherichia coli, as an example. Deployment of microarray strategies to assess closely-related microbial strains should help address diversity of organisms in their feral settings.